JWSS - Journal of Water and Soil Science

Factor analysis is one of the multivariate statistical techniques that considers the interrelationships between apparently irrelevant variables and helps researchers to find the hidden reasons for the occurrence of an event. In order to evaluate the effects of different irrigation levels and humic acid foliar application and identify the factors affecting water use efficiencies of sesame (Sesamum indicum L.), maize (Zea mays L.) and common bean (Phaseolus vulgaris L.), a split plots experiment based on RCBD design with three replications was conducted during the 2014-15 growing season, at the Research Farm of Ferdowsi University of Mashhad, Iran. Irrigation levels (50 and 100% of water requirement) and foliar application and non-application of humic acid were assigned to main and sub plots, respectively. The results showed that in sesame, the highest seed yield and biological yield were obtained from 100% of water requirement and humic acid spraying treatment. In maize, humic acid spraying under condition of supplying 50% of water requirement increased seed weight per plant, plant height, and leaf area index and soil pH In bean, the highest seed weight per plant, plant height, leaf area index, crop growth rate and soil phosphorous content were observed in the treatment of 100% of water requirement and humic acid spraying. Factor analysis results also showed that in sesame, the variables of seed yield, biological yield, seed weight per plant, plant height, leaf area index, crop growth rate, soil phosphorous and water use efficiency were assigned to the first factor and the variables of soil nitrogen, soil pH and EC were assigned to the second one. In maize, seed yield was assigned in the same group with the variables of biological yield, leaf area index, crop growth rate, soil phosphorous, EC and pH and water use efficiency; in bean, this was with the variables of seed yield and water use efficiency. In general, the research results revealed that identifying the effective variables in each factor and those logical nominations according to Eco physiological knowledge can lead to the direct management of effective variables with regard to associated factor, thereby leading to water efficiency improvement.

Exploring the homogenous regions for site specific management is important, especially in the areas under different anthropogenic activities. This was investigated using multi-way analysis including Factor Analysis, Hierarchical Clustering Analysis and k means in the areas under long-term wastewater irrigation over a period of more than 40 years, in Shahre Rey, south of Tehran. By using Factor Analysis model, eight factors as eight geochemical groups were extracted to explain approximately 60% of the total variance related to 37 soil physicochemical properties. The most important groups included the nutrient elements (OM, OC and N), micronutrients (Mn and B), soil water adsorption capacity (Clay, Silt, Sand and CEC), salinity and osmotic pressure (EC, OP and TDS) and sodification (SAR and Na). The maximum values of Cophenet and Silhouette coefficients were equal to 0.77 and 0.83, respectively, dictating the selection of the average linkage approach in Hierarchical Clustering Analysis and three clusters in the k-average method with 19, 24 and 34 mapping units. The Thiessen Polygons method in GIS was applied to separate the geochemical groups in the form of mapping units. This output, which was, in fact, the combination of multi-way models and its visual representation in GIS under separated mapping units of study area, could present suitable management activities for the areas under each cluster.